Time Series Analysis and Forecasting using ARIMA models in R

Описание к видео Time Series Analysis and Forecasting using ARIMA models in R

This R tutorial will help you understand the Basics of ARIMA Models in R. In this video, we will cover how to build a model from scratch. The ADF (Augmented Dickey-Fuller test) will be used to check the stationarity of the series. We will also use the PACF and ACF plots to identify the p and q term of the ARIMA Model.

Broad Topics are outlined below:

1/ Import Data/Change working Directory
2/ Covert Sales data into R time series object
3/ Check Stationarity
4/ Apply Differencing if not stationary
5/ Identify autoregressive term using PACF plot
6/ Identify moving average term using ACF plot
7/ Build ARIMA model using the arima() function
8/ Use forecast() function to forecast 12 months ahead
9/ Plot Time Series with Forecast

Code and Data Download: https://github.com/KunaalNaik/YT_Time...

#ARIMA #Forecasting #R #TimeSeriesAnalysis

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